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Chaos, Solitons and Fractals 139 (2020) 1100 5 2
Contents lists available at ScienceDirect
Chaos, Solitons and Fractals
Nonlinear Science, and Nonequilibrium and Complex Phenomena
journal homepage: www.elsevier.com/locate/chaos
Bibliometric method for mapping the state of the art of scientific
production in Covid-19
Mohamed El Mohadab
∗
, Belaid Bouikhalene , Said Safi
Laboratory of Mathematics Innovation and Information Technology (LIMATI), Department of Mathematics and computers Sciences, Polydisciplinary faculty
Beni Mellal, Sultan Moulay Slimane University, Morocco
a r t i c l e i n f o
Article history:
Received 3 June 2020
Accepted 23 June 2020
Available online 30 June 2020
Keywo rds:
Covid-19
Scientific production
Bibliometric method
Bibliometric analysis
Scientific research
a b s t r a c t
Global scientific production around the Covid-19 pandemic, in the various disciplines on the various inter-
national scientific bibliographic databases, has grown exponentially. The latter builds a source of scientific
enrichment and an important lever for most researchers around the world, each of its field and its po-
sition with an ultimate aim of overcoming this pandemic. In this direction, bibliometric data constitute
a fundamental source in the process of evaluation of scientific production in the academic world; bib-
liometrics provides researchers and institutions with crucial strategic information for the enhancement
of their research results with the local and international scientific community, especially in this interna-
tional pandemic.
© 2020 Elsevier Ltd. All rights reserved.
1. Introduction
The latest statistics indicate that there has been an exponential
increase in the number of publications since the discovery of the
Covid-19 pandemic; the results provide a comprehensive view of
interdisciplinary research in medicine, biology, finance and other
fields.
The number of publications in international databases aims to
disseminate and share the contributions and advances of academic
research from different groups of researchers from different uni-
versities and countries in the thematic of Covid-19.
Bibliometrics [1] is a tool for mapping the state of the art in a
field related to given scientific knowledge. So the use of bibliomet-
ric analysis [2] to identify and analyze the scientific performance of
authors, articles, journals, institutions, countries through the anal-
ysis of keywords and the number of citations constitutes an essen-
tial element which provides researchers with the means to identify
avenues and new directions in relation to a theme of scientific re-
search.
2. Bibliometrics at the service of scientific research
Scientometrics [3] is considered as the science of measurement
and the analysis of science which is based on an input set and an
output set which uses bibliometrics in the field of study of pub-
lications. The latter is a meta-science which takes science as its
∗Corresponding autho r.
E-mail address: m.elmohadab@gmail.com (M.E. Mohadab).
object of study based on three elements of scientific activity: its
inputs, its outputs and its impacts. Thus, it makes it possible to
map and broaden knowledge on a research field, by clarifying the
links between the authors, the publications, the institutions, and
other characteristics of the studied field.
Scientific publications [4] represent all publications in newspa-
pers or conferences, either chapters in scientific books or scientific
patents. All these types of publications represent the work of a re-
searcher who publishes these works with the aim of circulating
these results in databases which have broad international visibil-
ity and scientific credibility such as Web of Science, Scopus… and
renowned publishing houses such as Elsevier, Springer, Wiley, etc.;
but with all the effort s made, the benefit s that can be drawn re-
main limited if we cannot manage this large mass of publication
which is added every day to the thousands or millions of existing
scientific papers.
Bibliometric data is used for:
• Measure and compare the scientific output of the researcher,
research groups, institutions, regions or countries using indica-
tors based on:
- The number of publications.
- The quotes received.
- The collaborations.
• Identify the most important or influential journals in a given
field.
• Monitor the evolution over time of a discipline or research sub-
ject.
https://doi.org/10.1016/j.chaos.2020.110052
0960-0779/© 2020 Elsevier Ltd. All rights reserved.
2 M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052
Fig. 1. Statisti cs of the best author published for Covid-19 on Scopus.
These data represent the main part of the data provided for
each paper by the databases which allow bibliometrics to carry out
statistical processing, and bibliometric analysis.
3. Statistical overview on Covid-19
3.1. The international context
According to statistics provided by Johns Hopkins University
[5] until May 23, 2020, the death of more than 339,949 peo-
ple worldwide, was the infection of 5,267,452, considerable effort s
were made in the various disciplines relating to the treatment of
this pandemic either from near or far.
Since the beginning of the year, Covid-19 represents an increas-
ing interest for researchers from all over the world, in response to
this crisis, a lot of research was carried out in many fields of re-
search (medical, biology, financial, ...) by several Institutions and
organizations, either public or private worldwide, each with their
own means available.
By reviewing most of the scientific databases, the search to
identify the scientific output related to the subject of Covid-19
[6] was carried out using a set of terms as search criteria, the lan-
guage of the documents is the English because it is the universal
language of research, all disciplines are authorized in order to pro-
vide a global view of Covid-19 research in the various disciplines,
research is limited to the period from early 2020 (Beginning of the
pandemic a been listed) so far Figs. 1–17 .
❖ SCOPUS [7] :
Using the Scopus search engine to search for the word “covid-
19” a nd “coronavirus” from 01/01/2020 until 23/05/2020, we find
10,228 documents:
- According to the authors:
- According to the institutions:
- According to the country:
- According to the type of documents:
- According to the domains:
❖ Web of Science [8] :
Using the search engine of Web of Science to search for
the word “covid-19” and “coronavirus” from 01/01/2020 until
23/05/2020 results in 5,161 documents:
- According to the authors:
- According to the institutions:
- According to the country:
- According to the type of documents:
- According to the domains:
3.2. The African and Arab context
❖ Scopus:
Africa:
Arab:
❖ World of Science:
Africa:
Arab:
4. Methodology of the analysis of bibliometric data
The exploitation of the bibliometric parameters available on the
scientific data base on multiple field and discipline makes it pos-
sible to release relevant information which can meet the expec-
tations of researchers, research teams and research institutes. The
bibliometric analysis reveals to the researcher exact information
for the construction of new research as in the case of our study
on Covid-19.
M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052 3
Fig. 2. Sta tistics of the best 10 institutions published for Covid-19 on Scopus.
Fig. 3. Sta tistics of the best 10 countries published for Covid-19 on Scopus.
4 M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052
Fig. 4. Sta tistics of the type of document published for Covid-19 on Scopus.
Fig. 5. Domain statistics published for Covid-19 on Scopus.
This study was carried out on the basis of specific research us-
ing the three databases (Scopus, Web of Science, Pubmed) from
the beginning of 2020 until 23/05/2020. The sample consists of
5,161 academic publications (Web of Science), 10,228 academic
publications (Scopus) and 7,9 91 academic publications (Pubmed).
The use of bibliometrics will contribute to the exploration and
description of the existing scientific literature on the theme of
Covid-19.
The steps taken to achieve the desired results are manifested
as:
The use of bibliometric tools plays an important role in guiding
a particular field of study by collecting scientific data and synthe-
sizing the results obtained.
Statistics from different bibliographic databases which differ ei-
ther in terms of data volume or coverage constitutes a reliable
source for bibliometric indicators [9] .
M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052 5
Fig. 6. Sta tistics of the best 10 author published for Covid-19 on Web of Science.
Fig. 7. Statistics of the best 10 institutions published about Covid-19 on Web of Science.
Choosing the right database, the right keywords and applying
the filters that reflect the research objectives is a crucial step to
have reliable results.
Among the credible scientific database which brings together
most of the publishing houses known as Elsevier, Taylor & Fran-
cis, Springer…, we find Scopus, web of Science and for the medi-
cal field Pubmed [10] equipped with different filters to refine the
search and limit the results found.
Some researches try to analyze data coming from the various
scientific databases, but there are structural differences between
the platforms. Thus the differences in the classification of informa-
tion adopted by each of them builds an obstacle for an exploitation
of the common data.
For a good bibliometric analysis, we choose the following bib-
liometric data:
- Article title.
- Authors.
- Keywords.
- Number of citations.
- Yea r of publication.
- Journals.
- Type of documents.
- Institution.
- Country.
- Field of research.
6 M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052
Fig. 8. Sta tistics of the best 10 countries published about Covid-19 on Web of Science.
Fig. 9. Sta tistics of the type of document published about Covid-19 on Web of Science.
Regarding the indicators used by Scopus we find:
- H-index [11] : is based on the highest number of articles with
at least the same number of citations.
- CiteScore: measures the average number of citations received
per document published in the serial publication.
- SJR: measures the weighted citations received by the periodical,
the weighting of the citations depends on the domain and the
prestige of the citing series.
- SNIP: the standardized paper impact of the source which mea-
sures the actual citations received compared to the expected ci-
tations for the field of serial publication.
Regarding the indicators used by Web of Science we find:
- H-Index: the most used research indicator that measures both
the productivity and the impact of an author’s scientific pro-
duction.
- The impact factor: measures the importance of a review accord-
ing to the number of citations received in a year.
- Journal Citation Reports: Web of science product and an author-
itative resource for impact factor data.
In the present case study, the keywords employed are “Covid-
19” / “Coronavirus” from the beginning of 2020 (date of the
start of the pandemic). The search should focus mainly on the
M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052 7
Fig. 10 . Domain statistics published for Covid-19 on Web of Science.
Fig. 11 . Sta tistics of the best 10 African countries published for Covid-19 on Scopus.
titles, keywords and abstracts of articles in each of the databases.
Then the results found for each of the three databases (Scopus,
Web of science, Pubmed) builds our separate database on which
our bibliometric analysis will be applied. We export the data
from Scopus in format (.csv), Web of science, Pubmed in format
(.txt).
Next, we use the VOSviewer software [12] which represents a
high-performance solution with numerous viewing options with
co-quotation, co-word, co-author network analysis.
4.1. Identification and analysis of research trends on Covid-19
Through bibliometric analyzes we try to get the trends of sci-
entific research in the theme of Covid-19.
4.1.1. Analysis of authors, institutions and countries
In order to observe and evaluate the trends in publications in
the thematic of Covid-19, the VOSviewer software was used to an-
alyze the academic literature and examine the evolution of pub-
8 M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052
Fig. 12 . Statistics of the best 10 Arab countries published about Covid-19 on Scopus.
Fig. 13 . Statistics of the best 10 African countries published about Covid-19 on Web of Science.
lished articles, co-authorship, geographic area (country) of authors,
co-citation, co-occurrence.
The analysis of the authors belonging to the database al-
lows to have a global view on the authors active in the the-
matic by offering the possibility to follow the work of these
researchers by opening the door to achieve cooperation and
partnerships.
Thus, the analyzes of research institutions and countries con-
stitute an effective asset for finding the pillar institutions in each
field, with the aim of seeking possible cooperation at the level of
research institutions.
The software used for viewing and mapping the structure of
a research are including Bibexcel, Histcite, Citespace, Gephi, and
VOSviewer. For this work, we chose to work with VOSviewer be-
cause it allows us to easily display and interpret the display of
large bibliometric maps.
In order to carry out the various analyzes previously cited and
to examine the evolution of the articles published, we have for:
❖ Scopus:
- For authors:
We have 21 clusters distributed as follows:
Cluster 1-2: 42 items; Cluster 3: 29 items; Cluster 4-5: 27
items;
Cluster 6-7-8: 26 items; Cluster 9: 25 items; Cluster 10:
23 items;
M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052 9
Fig. 14 . Statistics of the best 10 Arab countries published about Covid-19 on Web of Science.
Fig. 15 . Stage of the proposed bibliometric method.
Cluster 11: 21 items; Cluster 12-13: 19 items; Cluster 14-15 : 16
items;
Cluster 16:15 items; Cluster 17: 14 items; Cluster 18: 13 items;
Cluster 19-20: 11 items; Cluster 21: 7 items.
The results clearly show that there are 21 groups of researchers
collaborating with each other.
- For institutions:
We have 1 cluster which contains 12 items.
We deduce that most institutions collaborate with each other
on an international scale and not at the regional or continental
level.
- For countries:
We have 9 clusters distributed as follows:
Cluster 1-2-3: 5 items; Cluster 4-5-6: 4 items; Cluster 7-8-9:
3 items.
As we see in Fig. 21 , the map indicates a large node represent-
ing China which means the great involvement of the Chinese giant
through these researchers in the various research fields related to
Covid-19.
❖ World of Science:
- For authors:
Bibliometric studies are used to identify networks of re-
searchers or to map the structure of researchers in a given research
area.
We have 9 clusters distributed as follows:
Cluster 1:46 items; Cluster2: 46 items; Cluster3: 20 items; Clus-
ter 4:16 items;
Cluster 5:15 items; Cluster 6:11 items; Cluster 7: 11 items; Clus-
ter 8: 10 items;
Cluster 9: 10 items.
The results clearly show that there are 9 groups of researchers
who collaborate. Two groups have a significant number of re-
searchers despite an exponential increase in the number of publi-
cations since the start of the pandemic, international collaboration
between the authors remains low.
- For institutions:
The network analysis of research institutions with the high-
est number of links in this area are the institutions of the
10 M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110 052
Fig. 16 . Aut hor co-authorship network in the “Network visualization” display mode.
Fig. 17. Autho r organizations network in the “Network visualization” display mode.
M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052 11
Fig. 18 . Country organizations network in the “Network visualization” display mode.
Fig. 19 . Aut hor co-authorship network in the “Network visualization” display mode.
12 M.E. Mohadab, B. Bouikhalene and S. Safi/ Chaos, Solitons and Fractals 139 (2020) 110052
Fig. 20. Author organizations network in the “Network visualization” display mode.
United States and China. In other words, the institutions in China
and the United States have the highest total liaison force for col-
laboration with various institutions from different continents.
We have 31 clusters distributed as follows:
Cluster 1:33 items; Cluster2: 31 items; Cluster3: 30 items; Clus-
ter 4:28 items;
Cluster 5-6: 27 items; Cluster 7-8: 25 items; Cluster 9-10: 24
items;
Cluster 11- 12 : 23 items; Cluster 13-14 : 21 items; Cluster 15-16:
20 items;
Cluster 17- 18: 16 items; Cluster 19-20: 15 items; Cluster 21: 14
items;
Cluster 22: 13 items; Cluster 23: 10 items; Cluster 24: 9 items;
Cluster 25-26: 7 items; Cluster 27: 6 items; Cluster 28-29-30-
31: 5 items.
From the results found, it can be deduced that geographic prox-
imity between institutions tends to strengthen the collaborative re-
lationships of institutions. Thus, it warns of the need to expand
cooperation in other regions, countries or continents.
- For countries:
The analysis of the network of countries is an important form
of analysis which makes it possible to visualize the most influential
countries in a given field of research, thus it exposes the degree of
scientific cooperation between the countries.
We have 11 clusters distributed as follows:
Cluster 1: 7 items; Cluster 2-3: 6 items; Cluster 4: 5 items;
Cluster 5: 4 items;
Cluster 6-7-8: 3 items; Cluster 9-10-11: 2 items.
As we can see in Fig. 18 , the map shows a large node represent-
ing the countries and regions with the highest number of publica-
tions: China, United States, Italy, England, France and Spain Figs. 19
and 20 .
❖ Pubmed:
- For authors:
We have 6 clusters distributed as follows:
Cluster 1:27 items; Cluster 2-3-4: 15 items; Cluster 5: 7 items;
Cluster 6: 4 items.
Fig. 21. Country organizations network in the “Network visualization” display mode.
M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052 13
Fig. 22. Author co-authorship network in the “Network visualization” display mode.
Fig. 23. Author organizations network in the “Network visualization” display mode.
The results clearly show that there are 6 groups of researchers
who collaborate with each other, a group has a large number of re-
searchers, followed by a group that is distinguished by the number
of researchers who compose them.
- For institutions:
In 1 cluster with 13 items, we notice that there is a significant
presence of Italian medical institutions, the analysis of data from
Pubmed by VOSviewer does not offer the possibility of analyzing
the network of countries.
4.1.2. Analysis of keywords
❖ VOSviewer:
We have 3 clusters distributed as follows:
Cluster 1: 6 items; cluster 2-3: 4 items.
The results found build a map dividing the keywords into three
groups with the minimum number of occurrences of a keyword
fixed at 6 elements for the first group and 4 elements for the sec-
ond and third group. The keyword "Coronavirus" has the highest
occurrence and total binding strength, other keywords with a high
occurrence include “Sars-cov-2”, “Covid-19” Figs. 22 and 23 .
❖ Wordl e [13] :
Among the existing display means, there is the word cloud
which is a practical tool allowing to have a dimensional visualiza-
tion of the keywords most used in the database. For our case, we
use wordle which is an analysis tool which makes it possible to
display a word cloud which gives greater importance to the words
which appear more frequently in the source text, for the three sci-
entific databases already mentioned, we find:
14 M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052
Fig. 24. Author keywords network in the “Network visualization” display mode.
Fig. 25. Wordle-generated image of the words Covid-19 for Scopus.
Fig. 26. Wordle-generated image of the words Covid-19 for Web of science.
M.E. Mohadab, B. Bouikhalene and S. Safi / Chaos, Solitons and Fractals 139 (2020) 110052 15
Fig. 27. Wordle-generated image of the words Covid-19 for Pubmed.
- Scopus:
- Web of Science:
- Pubmed:
From the Figs. 24–27 provided by VOSviewer and Wordle, a set
of words related to the pandemic such as (Covid-19, Coronavirus,
Sars-cov-2, 2019-ncon) as synonyms used in scientific literature, so
the appearance of terms (China, Wuhan, USA) refers to the place of
appearance of the pandemic and the countries that are conducting
research to find the vaccine, too (Medical, Health, Hospital, virol-
ogy) refers to the most concerned research area, (Zhang, Wang) for
the most productive researchers in the topic of Covid-19 in scien-
tific databases.
5. Conclusion
Since the onset of the pandemic, considerable effort has been
invested by researchers worldwide depending on the fields and re-
sources available, an exponential increase in scientific production
has been recorded in the various databases around the Covid-19.
In this work, we opted for a statistical study for the data from
the bibliographic databases Scopus, Web of Science for the theme
of Covid-19. The scientific contribution of researchers from the USA
and China shows a total involvement of institutions from these
two countries, so for the African continent researchers from "South
Africa and Egypt are the exception, while for the Arab region Saudi
Arabia and Egypt are leading the effort s of the Arab countries for
this pandemic.
Afterwards, a bibliometric analysis method was adopted in or-
der to map the state of the art on the theme of Covid-19, so the
three scientific databases (Scopus, Web of Science, Pubmed) were
used. Thus, the search must be precise and planned by combining
the precision of the terms to be used and adequate filters to re-
fine the results found, in order to conduct a relevant bibliometric
analysis by analyzing the contributions of the authors, institutions,
countries and the words- keys.
Finally, it is well known that the method presented remains ap-
plicable for other scientific themes and not only for the Covid-19
theme, it should be noted that the results obtained with the ap-
plication of the proposed method may vary depending on the ba-
sis of scientific data chosen and the appropriate filters in order to
present the evolution of published articles, co-authors, geographic
area of the authors, co-citation, co-occurrence analysis and key-
words.
Declaration of Competing Interest
We wish to draw the attention of the Editor to the following
facts which may be considered as potential conflicts of interest and
to significant financial contributions to this work. [OR] We wish
to confirm that there are no known conflicts of interest associated
with this publication and there has been no significant financial
support for this work that could have influenced its outcome. We
confirm that the manuscript has been read and approved by all
named authors and that there are no other persons who satisfied
the criteria for authorship but are not listed. We further confirm
that the order of authors listed in the manuscript has been ap-
proved by all of us. We confirm that we have given due considera-
tion to the protection of intellectual property associated with this
work and that there are no impediments to publication, including
the timing of publication, with respect to intellectual property. In
so doing we confirm that we have followed the regulations of our
institutions concerning intellectual property.
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